Daily load curve forecasting via automatic selection of models

A daily load curve forecasting method is proposed. In the method, the best load model is selected automatically based on a criterion, and the special days effect on the load is classified and modelled. Thus the authors can treat the time varying nature of the load and special days effect in a suitable and effective way. There exist various kinds of factors which have influences on the load but not included in the models here, e.g., weather, humidity and economic situation. >